Milvus has launched Milvus Lite, a new lightweight version of its vector database, now available on Product Hunt. The Python-native Milvus Lite is designed to run on edge devices and in notebooks, simplifying the development of applications utilizing vector search. The integration with BentoCloud allows for the deployment of inference services for embeddings and querying. Milvus Lite can be easily installed using pip-install, making it accessible for developers to prototype and migrate to production seamlessly using the shared API. The launch has garnered support from various partners, including LangChainAI and the MLOps Community.
Check out the sample notebooks to see how simple the Milvus Lite setup is. 👇 In case you didn't hear, Milvus Lite is a new pip-installable version of the @milvusio open source vector database that makes it easy to run on your laptop or notebook. https://t.co/Q1WcEepqsC
Curious to get started with the new Milvus Lite but don’t know where to start? Never fear! @stephenbtl walks you through a basic vector search in under 2 minutes. ⏱ We also have example notebooks for retrieval augmented generation (RAG) and image search. RAG Notebook:… https://t.co/LIJPUcs5YW
Check out Milvus Lite on Product Hunt today! Please support and share feedback for the @milvusio team. https://t.co/3wfCfDyqUF
Milvus Lite, the latest lightweight version of Milvus is live on Product Hunt! Show your support for this new pip-install version and leave your feedback 👉 https://t.co/YLgaFz28ob #producthunt #vectordatabase #milvus https://t.co/d0rzJZ9DjN
huge shoutout to the new milvus release. very thankful to have them as a sponsor of the MLOps Community! Go check out milvus lite! https://t.co/hN5we1OAzP
Excited to be part of the Milvus Lite launch! Together, we're simplifying the creation of powerful GenAI apps. Discover how our combined capabilities can elevate your AI projects. ✍️ Read the blog from @milvusio: https://t.co/h3zEdtA4Sn 📓 Check out the docs:… https://t.co/aLsutiHEch
The rise of #LLMs has made vector embeddings and #VectorDB immensely popular and useful, particularly in #AI, #GenerativeAI, and #LLMOps applications. 🌟💯🌟 @bindureddy from @abacusai explains in this “RAG - Vector Retrieval - Comprehensive Study”… ⬇️⬇️ https://t.co/dIzKtFBzXv
🎉 A new Milvus is here! Milvus Lite is an easier way to get started with vector search. Simply pip-install pymilvus on your laptop or notebooks. When you’re ready to migrate your prototype to production, the shared API makes it easy. Learn more 👉 https://t.co/HldZwszDTZ https://t.co/G2gwCVC1dH
💡 The integration between @milvusio Lite and #BentoCloud provides another way to build #RAG! In this blog post (https://t.co/pWLLsVeJQp), we use pre-built Bentos on #BentoCloud to deploy inference services for embeddings and querying, with Milvus Lite as the vector database. 👀…
💡 The integration between @milvusio Lite and #BentoCloud provides another way to build #RAG! In this blog post, we use pre-built Bentos on #BentoCloud to deploy inference services for embeddings and querying, with Milvus Lite as the vector database. See this link to learn more:…
🤝 Excited to be a launch partner to @milvusio lite! Milvus lite is a python native and - as the name might give away - lightweight version of the popular vector database. It's made to run on edge devices and in notebooks. 👇 Cookbook to get started below https://t.co/VO4WaSQGQ9
Milvus Lite, our brand new, pip-install, lightweight version of Milvus is live on Product Hunt! Show your support and leave your feedback 👉 https://t.co/YLgaFz28ob #producthunt #vectordatabase #milvus https://t.co/6hdViAL9Y8
10 Challenges in Building RAG-Based LLM Applications https://t.co/0eGgRVoUje
Powered by Groq, @Vectorizeio delivers a powerful Retrieval Augmented Generation (#RAG) experimentation and pipeline platform. Read more here: https://t.co/j5EIDm4DFR
How RAG Apps Work with LLMs? RAG (Retrieval Augmented Generation) is a method to enhance the performance of LLMs like GPT-4o, Llama-3, Claude, Gemini, etc by combining retrieval mechanism with generation capabilities. Ever wondered how RAG apps combine retrieval and generation… https://t.co/FyJfQyTdxG
Retrieval Augmented Generation (RAG) enables generative models to source answers quickly and accurately from large data-sets. In our latest edition of Building the AI Workforce, Satya Borgohain shares his insights and learnings from helping build a world-class RAG…